Brigham Young University BYU ScholarsArchive eses and Dissertations 2019-06-01 Management of Global Reservoir Sedimentation: Evaluating RESCON 2 for Sediment Management Alternatives Christopher Jacob Garcia Brigham Young University Follow this and additional works at: hps://scholarsarchive.byu.edu/etd is esis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in eses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. BYU ScholarsArchive Citation Garcia, Christopher Jacob, "Management of Global Reservoir Sedimentation: Evaluating RESCON 2 for Sediment Management Alternatives" (2019). eses and Dissertations. 7505. hps://scholarsarchive.byu.edu/etd/7505
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Brigham Young UniversityBYU ScholarsArchive
Theses and Dissertations
2019-06-01
Management of Global Reservoir Sedimentation:Evaluating RESCON 2 for Sediment ManagementAlternativesChristopher Jacob GarciaBrigham Young University
Follow this and additional works at: https://scholarsarchive.byu.edu/etd
This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by anauthorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected].
BYU ScholarsArchive CitationGarcia, Christopher Jacob, "Management of Global Reservoir Sedimentation: Evaluating RESCON 2 for Sediment ManagementAlternatives" (2019). Theses and Dissertations. 7505.https://scholarsarchive.byu.edu/etd/7505
Management of Global Reservoir Sedimentation: Evaluating RESCON 2 for Sediment Management Alternatives
Christopher Jacob Garcia
Department of Civil and Environmental Engineering, BYU Master of Science
Reservoir sedimentation occurs as dams impound streams and rivers, preventing the
delivery of sediments downstream. Globally, reservoirs lose approximately 40 million acre-ft of storage to sediments each year. Several methods for managing reservoir sedimentation have been developed to help extend project life. In 2017, the World Bank sponsored REServoir CONservation (RESCON) 2, a pre-feasibility program aimed to help users select sediment management practices to consider for more detailed studies.
There are two main objectives to this research: 1) perform a sensitivity analysis to
understand which parameters require greater precision and which can be roughly approximated, and 2) evaluate RESCON 2 suggested practices to assess the model’s accuracy and consistency for providing the optimal solution. Comparisons of the actual sediment management practice will be made with RESCON’s results and applicable zones from the Sediment Management Options Diagram (SMOD). Brief descriptions of the SMOD and RESCON 2 will be provided. RESCON-required inputs will be summarized, and some key entries will be presented. Additionally, innovations taken in Japan to modify and retrofit exiting reservoirs with sediment management capabilities will be explored.
The sensitivity analysis proves the unit benefit of reservoir yield parameter to be highly
sensitive, and users should invest time into determining this value. The sensitivity analysis also illustrates certain processes in RESCON, such as automatically determining the implementation schedule of flushing or a sustainable solution for dredging operations, have great influence over the respective method’s analysis. Approximations can be used if these options were selected.
Twenty reservoirs from around the world were modeled in RESCON 2, with storage
capacities ranging between 152 acre-ft and 31.9 million acre-ft. All sediment management alternatives whose NPV lied within 30% of the highest alternative were deemed practicable for the reservoir. Of the twenty models analyzed in RESCON 2, ten did not practice sediment management. Analyzing only those reservoirs where sediment management is being employed, RESCON predicted the correct or used practice eight out of ten times.
Recommendations to improve RESCON include 1) an HSRS operations and maintenance parameter, 2) expanding the unit benefit of reservoir yield parameter into several terms to more explicitly state applicable revenue sources, and 3) creating a list of RESCON model builds, updates, and bug treatments and an option for users to report bugs or other problems. Keywords: reservoir sedimentation, sediment management, RESCON, reservoir conservation
ACKNOWLEDGEMENTS
I would like to first thank my mentor, Dr. Rollin Hotchkiss, for his invaluable feedback
and guidance throughout my research; for providing me opportunities to travel abroad and
experience firsthand the brilliance of our colleagues and their work; and for exemplifying
professionalism as both a teacher and friend.
As part of my graduate committee, I would like to thank Dr. Dan Ames and Dr. Jim
Nelson for their feedback and critique. Additionally, I would like to thank them for their years of
help and assistance throughout my undergraduate and graduate experience at BYU.
I would also like to thank George Annandale, Paul Boyd, and Nikolaos Efthymiou for
providing information to help me better understand, execute, and analyze RESCON, and Razieh
Anari for helping me run sensitivity analyses on RESCON.
Lastly, I would like to thank my wife, Missy, and our family members and friends.
Whether cooking and providing me meals, staying overnight with me at the hospital, or helping
me relax with games and other fun activities, their time and love has helped me beyond
expression. Thank you!
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TABLE OF CONTENTS List of Tables ................................................................................................................................ vii
List of Figures .............................................................................................................................. viii
LIST OF TABLES Table 2-1: Sediment-Related Consequences of Dam Construction (Hotchkiss and Bollman
1996) ........................................................................................................................................ 6 Table 3-1: Summary of Sediment Management Alternatives Used in RESCON 2 ..................... 11 Table 3-2: RESCON vs RESCON 2 Sediment Management Options ......................................... 13 Table 3-3: RESCON Required Inputs........................................................................................... 13 Table 4-1: Reservoirs Analyzed in RESCON 2 ............................................................................ 23 Table 4-2: Default Values Used in Converting RECON Models Into RESCON 2 ...................... 24 Table 4-3: SMOD Data for Modeled Reservoirs .......................................................................... 25 Table 4-4: RESCON 2 Comparison of Results for Tarbela Reservoir ......................................... 28 Table 5-1: Sensitivity Testing in Tarbela Reservoir Model (1-highly sensitive, 2-sensitive, 3-
slightly sensitive, 4-negligible difference) ............................................................................ 29 Table 5-3. Actual Practice vs Acceptable RESCON Practices and SMOD Zone Predictions ..... 34 Table 6-1: Sensitivity Testing on Automatic Calculation Process ............................................... 37 Table 6-2: Amount of Sediment Dredged Sensitivity Analysis (1-highly sensitive, 2-sensitive,
3-slightly sensitive, 4-negligible difference) ......................................................................... 37 Table 7-1: Potential Expansion of Unit Benefit of Reservoir Yield ............................................. 44
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LIST OF FIGURES
Figure 2-1: Global pattern of suspended sediment yield (Walling and Webb 1983) ..................... 4 Figure 2-2: Dam density (Hossain et al. 2012) ............................................................................... 4 Figure 2-3: Comparing dam density with erosion-prone areas ....................................................... 5 Figure 2-4: Reservoir sediment deposition schematics (Ketelsen et al. 2013) ............................... 6 Figure 2-5: Sediment deposition in Lake Mead (NPS 2015) .......................................................... 7 Figure 2-6: Sedimentation in Lake Mead (NPS 2015) ................................................................... 8 Figure 3-1: Categorization of reservoir sedimentation countermeasures (Schellenberge et al.
2017, adapted from Annandale 2013) ................................................................................... 16 Figure 3-2: Map of Miyazaki Prefecture, Japan ........................................................................... 17 Figure 3-3: Mimi River basin (Sumi et al. 2015).......................................................................... 18 Figure 3-4: Slope failure downstream of the Tsukabaru Dam (Sumi et al. 2015) ........................ 18 Figure 3-5: New sediment sluicing operation (Sumi and Kantoush 2016) ................................... 19 Figure 3-6: Dam retrofitting for Yamasubaru and Saigou Dams (Sumi et al. 2015) .................... 20 Figure 3-7: Results of riverbed fluctuation analysis (Sumi and Kantoush 2016) ......................... 21 Figure 4-1: SMOD with zones of applicability and RESCON-analyzed reservoirs ..................... 26 Figure 5-1: Comparison of predicted alternatives, all cases ......................................................... 32 Figure 5-2: Comparison of predicted alternatives, only reservoirs practicing sediment
management considered ........................................................................................................ 33 Figure 6-1: SMOD with only Millsite Reservoir .......................................................................... 40
1
1 INTRODUCTION
Reservoir sedimentation is the process by which reservoirs lose their storage capacity to
sediments over time, and occurs as dams impound streams and rivers, changing the natural flow
regime and preventing sediment delivery downstream. The worldwide annual storage loss due to
sedimentation is between 0.5- and 1%, accounting for some 40 million acre-ft (50 km3)
(Mahmood 1987; Basson 2009). This problem is compounded by the fact that the “worldwide
annual loss of storage to sedimentation is higher than the increase of capacity by construction of
new reservoirs.” In order to preserve and restore storage capacity, both for existing and future
reservoirs, “mitigation measures are urgently needed” (Schleiss et al. 2016).
When reservoir sedimentation was beginning to receive attention, few methods for
managing inflowing sediments existed. In the 1930s, engineer and consultant J.C. Stevens urged
people to conduct an “intensive study and an intelligent research that will ultimately effect a
practical solution” (Nordin 1991). Later, in the 1970s, the ASCE Sedimentation Engineering
manual stated, “In an age that has progressed from the first automobile to a landing on the moon
in much less than a 100-year span, it is possible that in time either the reservoirs of today will no
longer be needed or that more effective methods of retaining their capacity will be developed”
(Vanoni 1975). Since Stevens’ time and that landmark statement from the ASCE, several
sediment management alternatives have been developed, and more effective means will
2
eventually surface. Consequently, over time, the dilemma has shifted from how to manage
sediments to which method to choose.
In response to the need to actively manage sediments in reservoirs, and with the advance
of technology and a greater understanding of sedimentation characteristics, in 2017 the World
Bank sponsored REServoir CONservation (RESCON) 2, an Excel-based program currently in its
beta development stages but expected to be finished over the next two years (Efthymiou,
personal communication, 2019). RESCON can analyze up to nine alternatives and attempts to
help users and analysts select practices to consider for more detailed studies. Upon inputting
required information into and running the program, a pre-feasibility analysis is provided
comparing the nine alternatives side-by-side. This analysis identifies practicable solutions for the
reservoir, whether each method is sustainable or non-sustainable, its net present value, and the
long-term reservoir storage capacity and reservoir lifetime. There are two main objectives for
this research: 1) perform a sensitivity analysis on RESCON 2 input parameters to determine
which variables need more accurate data and which can be roughly approximated; and 2)
evaluate RESCON 2 suggested alternatives to assess the model’s accuracy and consistency for
providing the optimal solution.
3
2 RESERVOIR SEDIMENTATION
Reservoir sedimentation occurs in every reservoir, but the fill rate varies significantly
depending on its geographic region. Figure 2-1 illustrates the global pattern of suspended
sediment yield in tonnes/km2/year. Locations receiving the highest sediment delivery are the
western Americas, southeast Africa, southern Europe, and southeast Asia. Ironically, these
erosion-prone regions correlate with locations having high dam density. Figure 2-2 shows the
number of dams per million sq. km on the basis of the GRanD database. Dams are defined as
having more than 0.1 km3 storage capacity, however, smaller reservoirs were included if data
were available (Lehner et al. 2011). Figure 2-3 transposes Figure 2-1 on top of Figure 2-2 to
demonstrate the relationship between sediment yield and dam density. The fact that many of the
world’s reservoirs lie within these areas is one reason why storage loss and storage preservation
is a topic of increased focus and concern.
Local Impacts of Dams
All rivers carry sediment from upstream to downstream and ultimately into either lakes or
oceans. When a dam is constructed, it alters the natural flow regime of the river and prevents the
delivery of sediments to the downstream river. A list of repercussions resulting from dam
construction are presented in Table 2-1, both up- and downstream of the reservoir, as well as
within. Impacts are distinguished by primary, secondary, and tertiary impacts. Other sediment-
4
Figure 2-1: Global pattern of suspended sediment yield (Walling and Webb 1983)
Figure 2-2: Dam density (Hossain et al. 2012)
5
Figure 2-3: Comparing dam density with erosion-prone areas
related consequences include coastal and shoreline erosion for beaches (Kondolf 1997; Pilkey et
al. 1992; Slagel and Griggs 2006), sediment abrasion on turbines (Auel et al. 2016), and the
plugging of dam outlet works (Randle et al. 2017). Greater detail about sedimentation
consequences is provided in Palmieri et al. (1998), Morris and Fan (1997), and Annandale
(2006).
Deposition Characteristics
Flowing waters possess a certain amount of sediment-carrying capacity or power. This
power dissipates when water enters the reservoir, leaving the majority of sediments to
accumulate at the reservoir headwaters and form a delta, while finer materials propagate toward
the upstream face of the dam. Figure 2-4 illustrates this phenomenon in a general sense, and
Figure 2-5 and Figure 2-6 provide an example from Lake Mead Reservoir, USA, impounded by
Hoover Dam. Near the headwaters of Lake Mead, sediment deposition is between 250- and
6
300-ft thick. The next several miles contain between 50- and 75-ft of deposited material. The
tributary feeding into Lake Mead—the Virgin River—has between 0- and 10-ft of deposition.
Table 2-1: Sediment-Related Consequences of Dam Construction (Hotchkiss and Bollman 1996)
Figure 2-4: Reservoir sediment deposition schematics (Ketelsen et al. 2013)
7
Figure 2-5: Sediment deposition in Lake Mead (NPS 2015)
8
Figure 2-6: Sedimentation in Lake Mead (NPS 2015)
Consequences for Future Generations
Annandale (2013) described reservoirs as either an exhaustible or renewable resource,
either of which is decided by how the dam is designed and operated. For instance, reservoir
storage space is considered an exhaustible resource if the rate of consumption (i.e., capacity loss
to sedimentation) exceeds the rate of replenishment, or the rate at which storage capacity can be
restored or added to. “Similarly,” Annandale states, “if a decision were made to manage
reservoir sedimentation by preventing or minimizing storage loss, the characterization of the
storage space changes from exhaustible to renewable.”
Hoover Dam
Reservoir headwaters
Tributary
9
Intergenerational equity is defined as meeting and satisfying the needs of present
generations without compromising the ability of future generations to meet theirs (Summers and
Smith 2013). Sedimentation will eventually make reservoirs obsolete and place future
generations with less desirable locations to construct new dams. Some estimates postulate that as
much as one-quarter of all dams will lose their storage capacity to sedimentation within the next
50 years (Schleiss et al. 2016). Conscious decisions made toward mitigating the effects of
reservoir sedimentation will ultimately determine if reservoirs will be classified as exhaustible or
renewable; if it will meet only present needs or be perpetuated to benefit others.
10
3 RESERVOIR SEDIMENT MANAGEMENT
Many of the adverse effects experienced via reservoir sedimentation can be mitigated
through appropriate countermeasures. The two most useful approaches for considering sediment
management alternatives are the RESCON program and using a graph called the Sediment
Management Options Diagram (SMOD). Each will be explained. Additionally, innovations taken
in Japan to manage sedimentation will be explored.
Sediment Management Alternatives
There are several methods for managing sedimentation in reservoirs. Table 3-1 outlines
the nine most commonly used alternatives, with descriptions taken from the RESCON 2 manual
(Efthymiou et al. 2017). For a more descriptive analysis of the various alternatives, see Kondolf
et al. (2014).
3.1.1 Effects of Sediment Management
Through the appropriate selection, implementation, and operation of reservoir
sedimentation countermeasures, many adverse effects can be controlled and even resolved. Auel
et al. (2016) showed three cases in Japan where sediment management helped prolong the useful
of the Asahi, Nunobiki, and Dashidaira Reservoirs by 440-, 1,200-, and 180-years, respectively.
Kondolf (1997) demonstrated how artificial sediment replenishment to the Rhine River helped to
11
prevent further channel incision below the Barrage Iffezheim Dam in France and Germany, and
in other locations was implemented to restore spawning habitats for fish. However, not every
response to sediment management will be positive. As Coker et al. (2009) commented, “No
solution to the sedimentation problem will be without compromise of competing values.”
Quadroni et al. (2016) recorded local ecological impacts following a flushing operation from the
Madesimo Reservoir in Northern Italy. Among other reactions, it was noted that the benthic
community closer to the reservoir did not recover to its pre-flushing condition 1-year after the
flushing operation. Analyzing and understanding all aspects of reservoir sedimentation and
sediment management will minimize negative consequences and maximize desired outcomes.
Table 3-1: Summary of Sediment Management Alternatives Used in RESCON 2
Sediment Management Practice Description No Action No sediment management plan implemented Catchment Management Reduce the sediment inflow into the reservoir Sluicing The reservoir volume is partially reduced
during the flood season, increasing the flow velocity
Sediment Bypass Tunnel The diversion of sediment-laden flows before the transported sediment load is deposited within the reservoir
Density-Current Venting The turbidity transported in reservoirs by means of density currents
Flushing Remobilization of deposited sediments by increasing the flow velocity in the reservoir
HSRS* Energy for the dredging operation is supplied by the hydrostatic head at the dam
Dredging Removes sediment by pumping water entrained sediment from the reservoir bed
Trucking The removal of accumulated sediment from a drained reservoir using heavy equipment
* Hydrosuction sediment-removal systems
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RESCON: A Brief History
Originally published in 2003, RESCON was created with the purpose of providing users
with a rapid assessment and pre-feasibility analysis of sediment management alternatives
(Palmieri et al. 2003). As understanding of the different alternatives developed and future effects
of climate change improved, the World Bank was prompted to update the RESCON model.
Commenting on the objective of the new RESCON 2 model, Annandale et al. (2017) noted it
was “to assess the technical viability and economic optimality of reservoir sedimentation
management alternatives at policy and pre-feasibility level,” and clearly stated it was “not
intended for feasibility and design phases of projects.”
The original RESCON only included assessments of flushing, hydrosuction-sediment
removal systems (HSRS), dredging, and trucking. Since then, sediment routing and inflow
reduction practices have been added (see Table 3-2). In addition to new sediment management
strategies, RESCON 2 improved on its economic analysis and added an additional feature
assessing climate change effects on reservoir sustainability (Annandale et al. 2017). The
economic analysis can consider various implementation schedules for sediment management
strategies and optimizes timing or recurrence to produce the highest net present value (NPV).
The climate change assessment is comprised of multiple steps which are documented in the
RESCON 2 user manual. To summarize, RESCON analyzes possible future climate scenarios
and selects a set that “spans the full range of climate futures,” and evaluates the different
sediment management strategies under these potential conditions (Efthymiou et al. 2017).
13
Table 3-2: RESCON vs RESCON 2 Sediment Management Options
Original RESCON RESCON 2 Flushing Flushing Trucking Trucking Dredging Dredging
Table 3-3 illustrates the six input worksheets within RESCON 2, the number of inputs for
each worksheet, and some key entries found therein. In total, there are 233 input parameters in
RESCON 2. However, note the sediment management page does not require all 80 inputs to run,
as not all sediment management options need to be analyzed. Also, some values can be
empirically estimated using functions built into the program, such as the mean annual sediment
inflow and the unit cost of dredging.
Table 3-3: RESCON Required Inputs
Page Name Number of Inputs Key Entries Project Definition 9 Required reliability of water supply Environmental Safeguard 97 Allowable environmental and social damage Reservoir Geometry 12 Storage capacity (live and dead), pool and bed elevations Hydrology and Sediment 26 Mean annual runoff and sediment inflows Economic Parameters 9 Unit cost of construction, discount rate, unit value of
reservoir yield, maximum duration of financial analysis Sediment Management 80* Allowable loss, year of implementation, frequency of
events Total: 233
*Maximum of 80, but fewer can be used if not analyzing all practices
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RESCON 2 Limitations
The RESCON 2 user manual lists the main limitations to the program (Efthymiou et al.
2017, pp. 5-6). Among these are its empirical-based approach and incomplete evaluation of
with a time step to successively fill the reservoir with sediment. The trapping efficiency is
updated with the new volume and the process repeats itself. In this way, an empirically based
sediment front fills the reservoir. The problem with this method is it is not site specific. The
annual sediment and water inflows, storage (dead and active) capacities, and certain other
variables are site specific, however, RESCON treats reservoirs as linear and is unable to simulate
multiple branches, and water and sediment inflow to the reservoir is treated as entering at the
headwaters. Additionally, the calculation of water yield is based on an empirical method, which
does not account for the operational rules of the reservoir. With regards to RESCON’s
environmental analysis, the manual states: “Despite scientific progress in environmental science,
no generic cause-effect relationships exist between changes in sediment flows and environmental
quality that can be incorporated in a pre-feasibility level mathematical model such as RESCON”
(pp. 137-138).
Sediment Management Options Diagram
There has been some debate as to the origins of the SMOD. It has traditionally been
referred to as the “Basson Diagram” (see Palmieri et al. 1998; Aras 2009); however, Dr. Basson
stated he used work previously done by Chinese researchers to develop his graph, and agreed the
name “Sediment Management Options Diagram” would be an appropriate title for the chart
(Basson, personal communication, 2018).
15
The SMOD relates water and sediment inflows to storage capacity in a graphical format
(Figure 3-1). The x-axis represents the reservoir storage capacity divided by the mean annual
inflow. This ratio is indicative of the hydraulic retention time (HRT), or the amount of time
water remains in the reservoir before passing downstream. A low HRT value would mean water
can fill the reservoir many times each year. The y-axis is the storage capacity divided by the
mean annual sediment inflow and can be interpreted as the reservoir’s life expectancy (Auel et
al. 2016). This ratio does not perfectly represent the lifetime of a reservoir, as reservoirs tend to
fill more slowly over time as storage capacity is lost (Morris and Fan 1997). Thus, the SMOD is
a somewhat simplistic approach to consider sediment management strategies, but, like RESCON,
it is meant to be used at the pre-feasibility stage and provides useful feedback and information.
In practice, the x- and y-coordinates of an existing or future dam is plotted on the SMOD
to determine which sediment management alternatives might merit more investigation.
Experience has shown that the various alternatives are effective for only a limited range of x- and
y-values, as demonstrated in Figure 3-1.
Innovations in Japan
During June 2018, a trip was taken to tour several Japanese dams and observe local
sedimentation problems and actions taken to mitigate their effects. Dr. Tetsuya Sumi and Dr.
Sameh Kantoush, along with Dr. Sumi’s graduate student, Koshiba Takahiro, kindly provided
and guided many visits, with stops at the Kurobe, Koshibu, Dashidaira, Yamasubaru, Saigo, and
Ouchubaru Dams. The latter three are part of a cascading series of dams located in the Miyazaki
Prefecture (Figure 3-2), lying along the Mimikawa (Mimi) River (Figure 3-3).
16
-Saigou -Yamasubaru
Figure 3-1: Categorization of reservoir sedimentation countermeasures (Schellenberge et al. 2017, adapted from Annandale 2013)
17
Figure 3-2: Map of Miyazaki Prefecture, Japan
18
Figure 3-3: Mimi River basin (Sumi et al. 2015)
In September 2005, Typhoon 0514 (Nabi) devastated the Mimi River basin with more
than 500 landslides and 50 inches (1,300 mm) of rain over a three-day period, causing severe
damage to surrounding urban areas and flooding rivers and reservoirs with sediments and other
large debris. Figure 3-4 shows one landslide, approximately a quarter of a mile wide (400-m),
occurring just downstream of the Tsukabaru Dam.
Figure 3-4: Slope failure downstream of the Tsukabaru Dam (Sumi et al. 2015)
19
In response to the effects caused by Typhoon Nabi, Sumi et al. (2015) commented:
“In October 2011, Miyazaki Prefecture, the river administrator, compiled the ‘Mimikawa River Basin Integrated Sediment Flow Management Plan’ which is showing the current status of the complex Mimikawa River sediment problems and possible approaches to solve these problems while balancing flood control, water usage and environmental conservation. As part of the Management Plan, the Kyushu Electric Power Company, KEPCO, which is responsible for dam installation is aiming to restore the original sediment flow which has been trapped by dam reservoirs up until now, and has drawn up a plan for sediment sluicing operation at Yamasubaru, Saigou and Oouchibaru Dams.”
The sediment sluicing operation mentioned involved retrofitting the Yamasubaru and Saigou
Dams with larger and lower sluice gates. Figure 3-5 illustrates the change in operation from a
side view. The “Existing Operation” dam shows sediments forming a delta-like deposit toward
the reservoir headwaters, as explained in Section 2.2. Lowering the gates decreases the water
depth in the reservoir, allowing the dam to function more as a run-of-river dam, providing easier
passage of sediments downstream to the river and increasing flood control and protection.
Figure 3-5: New sediment sluicing operation (Sumi and Kantoush 2016)
20
Figure 3-6 shows the current states and artistic renditions of the Yamasubaru and Saigou
Dams following their modifications. Two of the center gates at Yamasubaru will be merged into
one and lowered by approximately 30.5-ft (9.3-m). At Saigou, the four middle gates will be
merged into two gates and lowered by approximately 14-ft (4.3-m) Retrofitting these dams was
projected to be complete by 2022 and June 2018, respectively.
Figure 3-6: Dam retrofitting for Yamasubaru and Saigou Dams (Sumi et al. 2015)
Sumi and Kantoush (2016) performed an analysis on Yamasubaru Dam demonstrating
the change in riverbed elevation upstream of the reservoir with and without sediment sluicing
over a 33-year period (Figure 3-7). Their results indicated the riverbed would increase by as
much as 14.8-ft (4.5-m), with an average increase of about 6.6-ft (2-m) projecting 6-km
upstream, if no maintenance were performed to manage inflowing sediments. Under sluicing
21
operations, the riverbed would essentially remain unchanged, with some aggradation in the
stream bed immediately upstream from the dam and degradation in other locations.
Figure 3-7: Results of riverbed fluctuation analysis (Sumi and Kantoush 2016)
The fact that these dams have been/are being retrofitted is extraordinary. Sumi and
Kantoush (2016) remarked this would be the “first time … an existing dam [in Japan] will be
retrofitted by the addition of a new sluicing function after 80 years of commissioning.” This is a
novel step for sediment management both in Japan as well as globally, as many of the existing
and soon-to-be built dams are planned and designed without consideration of sediment
management (Kondolf et al. 2014). Economically justifying modifications had to overcome 1)
initial costs of implementation and 2) loss of revenues from generating hydroelectricity while
installing the new sluice gates. However, by remodifying these dams, storage capacity will be
preserved, providing for more and longer production of hydroelectricity over time (De Miranda
and Mauad 2014) and better flood control capabilities (Pattanapanchai et al. 2002).
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4 METHODOLOGY
Compiling RESCON 2 Models
Gathering data to compose a RESCON 2 model required extensive work to connect with
outside sources. Table 4-1 lists all RESCON-analyzed reservoirs and sources used to develop or
obtain the model. Some models came preconfigured in RESCON 2, others had to be converted
from the original RESCON model into RESCON 2, while others were created from only data.
This also is shown in Table 4-1 under “Original Model Type.”
4.1.1 Conversion from Original RESCON Models into RESCON 2
When developing a RESCON 2 model from the original RESCON, default values for
certain parameters were used. RESCON 2 contains several more variables than the original
model, so insufficient data were encountered in every transfer. In general, the parameters not
included in the original RESCON models and their assumed values in RESCON 2 are listed
below in Table 4-2. However, as a pre-feasibility program, the goal of RESCON 2 is to provide a
rapid assessment of sediment management strategies to consider and evaluate under detailed
analyses. Acquiring requisite data for each model proved difficult as certain information is not
posted or publicly available. As more accurate data becomes available, these can be modified to
increase evaluations of RESCON 2; but, at least in this way, an initial investigation of RESCON
2 and its probability of suggesting the ideal alternative could be assessed.
23
Table 4-1: Reservoirs Analyzed in RESCON 2
Reservoir Source Original Model Type Abdel Karim Annandale, G.W. (2017) RESCON 2 Baira Annandale, G.W. (2019) RESCON Banja Adhikari, S. (2017) RESCON 2 Bin El Quidine Annandale, G.W. (2017) RESCON 2 Çubuk Aras, T. (2009) RESCON El Canadá Zamora, J. (2018) Data Gavins Point Boyd, P. (2019) RESCON, data Gebidem Annandale, G.W. (2019) RESCON Ichari Annandale, G.W. (2019) RESCON Iron Gate Annandale, G.W. (2017) RESCON 2 Kali Gandaki Annandale, G.W. (2017) RESCON 2 Kulekhani Shrestha, H.S. (2012) RESCON Millsite Hotchkiss, R.H. (2018) Data Mohammed V Annandale, G.W. (2017) RESCON 2 Sanmenxia Annandale, G.W. (2019); Wu, B. (2018) RESCON Sefid-Rud Annandale, G.W. (2019) RESCON Sidi Driss Annandale et al. (2017) RESCON Tarbela Annandale, G.W. (2017) RESCON 2 Three Gorges Annandale, G.W. (2019) RESCON Upper Karnali Annandale, G.W. (2017) RESCON 2
24
Table 4-2: Default Values Used in Converting RECON Models Into RESCON 2
RESCON 2 Parameter Units Description Assigned
Value ncomp - Number of reservoir compartments 5
ExceedT % Percentage of time exceeded 30 60 90 ExceedMAR % Percentage of mean annual water inflow 40 20 3 ExceedMAS % Percentage of mean annual sediment inflow 25 5 3
T_b % Duration of bedload transport (% of annual time) 5 Distribution - Distribution of annual inflows Lognormal
- - Application of declining discount rate? No
CycleNS Years Time interval between flushing events during the
1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
CycleS Years Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long
term reservoir capacity) 1
Cycle1DR Years Duration of phase (No dredging) 1 Cycle2DR Years Cycle length in phase 2 (Dredging operation) 1
Year HSRSstart Years Time of HSRS installation 1 Cycle1TR Years Implementation year (for trucking operation) 1 Cycle2TR Years Frequency of trucking operation 1
RESCON 2 Models Within the Sediment Management Options Diagram
Each RESCON-analyzed reservoir in this study was plotted on the SMOD. Data for each
reservoir is located in Table 4-3. The SMOD of Figure 4-1 has been divided into option zones
based on field experience (Annandale 2013; see Figure 3-1). Reservoirs lying within or near box
1 were assumed to use either flushing, sluicing, HSRS, or dredging; box 2 to use sediment
bypass tunnels, flushing, sluicing, dredging, density currents, trucking, or check dams; and box 3
to use density currents, catchment management or no action.
25
Table 4-3: SMOD Data for Modeled Reservoirs
Reservoir CAP (million m3)
CAP/MAR (years)
CAP/MAS (years)
Abdel Karim 11.3 0.24 68 Baira 2.4 0.0024 11 Banja 403 0.27 221 Bin El Quidine 1,508 1.4 285 Çubuk 7.1 0.25 118 El Canadá 0.187 0.00047 3.7 Gavins Point 580 0.020 129 Gebidem 9 0.021 24 Ichari 11.6 0.0022 7 Iron Gate 100 0.067 33 Kali Gandaki 7.7 0.00094 0.25 Kulekhani 85.3 0.62 113 Millsite 22.2 0.091 243 Mohammed V 726 0.97 75 Sanmenxia 9,640 0.22 6 Sefid-Rud 1,760 0.35 47 Sidi Driss 7.2 0.058 30 Tarbela 14,350 0.19 98 Three Gorges 39,300 0.090 98 Upper Karnali 17.9 0.0011 0.8
26
Figure 4-1: SMOD with zones of applicability and RESCON-analyzed reservoirs
4.2.1 Reading and Interpreting the SMOD
In Section 3.3, it was noted the x- and y-axes of the SMOD are used in practice to
determine feasible sediment management alternatives depending on where the reservoir lies on
the graph. To illustrate how reservoir lifetime and HRT can help determine appropriate solutions,
two examples will be explored. The first will look at the Ichari Dam, and the second Bin el
Ouidane Dam.
The Ichari Dam is a concrete gravity dam located on the Tons River in Uttarakhand,
India, has an HRT of 0.0022 years and a life expectancy of about 7 years. With a low life
expectancy and capability of filling the reservoir hundreds of times each year, sediment
0.1
1
10
100
1000
10000
0.0001 0.001 0.01 0.1 1 10
Res
ervo
ir L
ife, y
ears
(sto
rage
cap
acit
y/m
ean
annu
al s
edim
ent i
nflo
w)
Hydraulic Retention Time, years(storage capacity/mean annual runoff)
Flushing, Sluicing, HSRS,Dredging
Bypass, Flushing, Sluicing,Dredging, Density Current,Trucking, Check DamsDensity Current, CatchmentManagement, No Action
Does Not Practice Sed. Mgmt.
Flushing
Trucking
HSRS
Sluicing
Dredging
1
3
2
27
countermeasures such as flushing, which can use more water than other methods, may be used
without compromising water storage, assuming that adequate low-level outlets exist in the dam.
The Bin el Ouidane Dam is an arch dam located on the El Abid River in the Azilal
Province, Morocco. It has an HRT of 1.44 years and life expectancy of 285 years—quite distinct
and different from the Ichari Dam. It has an average annual runoff of more than 1 billion m3, but
its large capacity indicates the need to preserve water. Flushing generally requires a complete
drawdown of the reservoir, emptying any water storage to remove deposited sediments. If
flushing were to occur here, it would eliminate more than an entire year’s worth of water storage.
Flushing would probably be unrealistic in this scenario, and it would be more appropriate to
consider water-conserving strategies such as catchment management, density current venting, or
no action.
Evaluating RESCON 2 Results
There were two main objectives for this research: perform a sensitivity analysis on
RESCON 2 input parameters to determine which variables need more accurate data and which
can be roughly approximated; and 2) evaluate RESCON 2 suggested alternatives to assess the
model’s accuracy and consistency for providing the optimal solution. Climate change effects
were not included as part of this analysis. To address the first, several parameters were tested in
the Tarbela Reservoir model. A couple were taken from Table 4-2 to understand default
parameters (i.e., how effective was using a default value to assess RESCON). Other parameters
were selected because either RESCON does not offer empirical approximations to assist when
determining appropriate values or it was unclear what effect these terms would have on the
overall computation and analysis of the various sediment management alternatives.
28
For the second purpose, an economical range was selected for each reservoir, and all
practices that lied within that range were considered potential alternatives meriting further
investigation. To illustrate how practices were deemed acceptable based on its economic
appraisal, an example of RESCON’s comparison was taken from the Tarbela Reservoir and
shown below in Table 4-4. All results that lied within 30% of the highest NPV alternative were
considered potential alternatives. Dredging returned the highest NPV at roughly 298 billion
USD, and sluicing, flushing, and trucking were all within 30% (i.e., >208 billion USD) of its
value.
Table 4-4: RESCON 2 Comparison of Results for Tarbela Reservoir
Sediment Management Strategy Aggregate Net Present Value
Long Term Reservoir Gross Storage Capacity
Reservoir Lifetime
Technique Sustainability Action in case of storage elimination [Billion US$] [Million m3] [Years]
No Action Sustainable --
0 224 Non Sustainable
Decommissioning 187.2 Run-Of-River 187.3
Catchment Management
Sustainable -- 0 236 Non
Sustainable Decommissioning 191.2
Run-Of-River 191.3
Sluicing Sustainable --
192.3 >217 Non Sustainable
Decommissioning -- Run-Of-River 249.4
By-Pass Sustainable --
0 284 Non Sustainable
Decommissioning 176.2 Run-Of-River 176.2
Density Current Venting
Sustainable -- 0 196 Non
Sustainable Decommissioning 75.4
Run-Of-River 75.4
Flushing Sustainable 267.3
1,472 >300 Non Sustainable
Decommissioning -- Run-Of-River --
HSRS Sustainable --
N/A N/A Non Sustainable
Decommissioning -- Run-Of-River --
Dredging Sustainable 297.6
9,856 >300 Non Sustainable
Decommissioning -- Run-Of-River --
Trucking Sustainable 247.9
7,409 >300 Non Sustainable
Decommissioning -- Run-Of-River --
29
5 RESULTS
Sensitivity Test
A sensitivity analysis was performed on the Tarbela Reservoir model. The tested
parameters, their initial and changed values, and effects seen on the various practices are listed
below in
Table 5-1. Under the “Result” section, values between 1 and 4 were assigned depending
on how much change was observed. Results with a value of 1 were considered highly sensitive,
with an observed change greater than 50%; 2 indicates a sensitive change between 20- and 49%;
3 is a slightly sensitive change between 5- and 19%; and 4 indicates a negligible difference with
0-4% variation. HSRS was not considered technically feasible by RESCON 2 for Tarbela.
Table 5-1: Sensitivity Testing in Tarbela Reservoir Model (1-highly sensitive, 2-sensitive, 3-slightly sensitive, 4-negligible difference)
Parameter (Description) Units Original
Value Changed
Value Practice Result
NPV Long Term Storage Lifetime
Cv
(coefficient of variation of
annual run-off volume)
% 12 24
No Action 2 4 4 Catchment
Management 2 4 4
Sluicing 2 4 4 Bypass 2 4 4
Density Current 2 4 4 Flushing 2 4 4 Dredging 2 4 4 Trucking 2 4 4
* Models not had in possession but results were obtained via sources outlined in Table 4-1. Thus, other results may be considered practical under “RESCON Acceptable Alternatives”.
35
6 DISCUSSION
The following discussion will give emphasis to reservoirs using sediment management,
though some of the content may be applicable to reservoirs currently taking no action.
Implications from Sensitivity Analysis
The Cv parameter expresses the variability of annual flows and is determined by dividing
the mean annual water inflow with the standard deviation of incoming flows (Efthymiou et al.
2017). The higher its value implies greater dispersion around the mean annual flow. Increasing
this parameter resulted in 20- to 49% lower NPVs for all sediment management strategies, and
decreasing this parameter increased NPVs by 5-19%. If insufficient data were available to
determine the Cv, and users had to judge between under- or overestimating this parameter, a
lower value would likely result in a more moderate change compared to the actual value and its
results.
The percentage of mean annual water inflow (ExceedMAR) specifies the intra-annual
distribution of water inflow (Efthymiou et al. 2017). For example, a 58% exceedance probability
represents a relatively normal inflow that is exceeded 58% of all days in the flow record.
Increasing the exceedance probability to 88% indicates a low-flow level, while decreasing the
probability to 38% indicates a high-flow. Overall, changing this parameter had negligible
influence on sediment management strategies, except for sluicing and sediment bypass tunnel.
36
When increased to 88%, sluicing and bypass tunnel were both significantly impacted. However,
decreasing this value had, at most, a 19% effect on any sediment management strategy. If users
had to judge between selecting a higher or lower initial value for this parameter, a lower value is
likely to produce a closer response to the actual exceedance probability.
The unit benefit of reservoir yield (P1) resulted in highly significant changes for every
alternative’s NPV. However, the first test changed the parameter’s original value by one order of
magnitude and second by half an order (i.e., dividing by 5). To better understand how sensitive
this parameter was to change, another test was performed changing the original value from 0.1-
to 0.2-$/m3. All NPVs were still significantly impacted, with percent differences ranging
between 100- and 122%. This suggests users should invest time into accurately determining the
value of this parameter.
The other three analyses (i.e., duration of flushing after complete drawdown, dredging
operation phase, and amount of sediment removed per dredging event) were tempered by other
inputs in RESCON. For flushing, RESCON 2 has the option to determine the implementation
schedule of flushing through economic optimization, and dredging has a similar option to
automatically determine a sustainable solution. These processes seem to have a greater influence
over their respective strategy than any of the three inputs analyzed. This implies users do not
need to have specific or very accurate data for these parameters, which is symptomatic of a pre-
feasibility program. However, another test was performed for dredging marking “no” to the
automatic sustainable solution option and changing the value of removed sediment per event
from 100 Mm3 to 50- and 150 Mm3, as was done in the initial analysis. This is illustrated in
Table 6-1, and the results are shown in Table 6-2. The same designation of 1, 2, 3, and 4 to the
observed changes are used here as they were in Section 5.1. Notably, reservoir lifetime remains
37
unaffected regardless of the amount dredged; storage capacity, on the other hand, is significantly
impacted in all cases; and NPV varies.
Table 6-1: Sensitivity Testing on Automatic Calculation Process
RESCON Parameter Original Value Sensitivity Analysis Tests
Shall a sustainable solution be determined automatically? Yes No
Amount of sediment removed per dredging event (million m3) 100 100 50 150
NPV Long Term Storage Reservoir Lifetime Amount of
sediment dredged (Mm3)
100 50 150 100 50 150 100 50 150
Results 2 4 4 1 1 2 4 4 4
The option to automatically determine a sustainable solution requires a certain amount or
percentage of storage capacity be retained throughout the duration of financial analysis. In the
“Economic Parameters” worksheet of RESCON, users input a percentage to define the threshold
for non-sustainability. For Tarbela, this was 95%—or, in other words, if the reservoir lost 95% of
its initial storage capacity it would be considered non-sustainable. RESCON also prompts users
to define the maximum duration of financial analysis, which was 300 years in this case. Using
these two inputs, and when the automatic solution is used, RESCON adjusts the amount of
dredged material to maintain at least 5% of the storage capacity over 300 years.
38
Analyzing the results when the automatic solution process is turned off, RESCON uses
the amount of dredged material per event and mean annual sediment inflow to determine
reservoir lifetime. Under this scenario, the reservoir lifetimes appear unaffected, as illustrated in
Table 6-2. This is both true and wrong at the same time. The lifetimes under each scenario (i.e.,
100-, 50-, and 150 Mm3) were over 300 years, but the fact the reservoir lifetimes were above the
defined period of financial analysis does not mean reservoir lifetimes were altogether unaffected.
When changing the duration of financial analysis from 300- to 10,000 years, reservoir lifetimes
vary between 350- to more than 10,000-years. Thus, it is best to mark “no” to the automatically
determined sustainable solution when either accurate data is available or users are desirous to
obtain rough estimates of NPV, reservoir lifetime, and long term storage capacity. It is
recommended to mark “yes” when users are lacking information to portray this value and are
hoping to gain some idea of what amount of dredged material would provide a sustainable
solution.
Cases Not Captured
There were four cases where RESCON and the SMOD differed from the current practice
at the reservoirs, namely, the Kulekhani, Sidi Driss, Tarbela, and Upper Karnali Reservoirs. Each
of these reservoirs do not practice sediment management, however, it’s undetermined if the
reservoir operators and decision makers made a conscious decision to employ no management
technique or if there is just nothing being done. This is the main reason for focusing on reservoirs
currently practicing sediment management. For instance, none of these reservoirs have a lifetime
expectancy greater than 113 years, with the Sidi Driss and Upper Karnali Reservoirs having an
expected life of 30 and 0.75 years, respectively. Obviously, this is undesirable and certainly not
39
sustainable. When analyzed in RESCON 2 and the SMOD, practices are recommended which
differ from taking no action.
When considering only the reservoirs that practice sediment management, all ten cases
matched appropriate SMOD zones. RESCON 2 did not predict the correct alternatives for the
Millsite and El Canadá Reservoirs.
When analyzed in RESCON 2, the NPV of the actually used practice at Millsite
Reservoir (dredging) was approximately 36% lower than the highest NPV alternative (no action).
Figure 6-1 shows the SMOD with only Millsite. It lies near the border of zone 3, where density
current, catchment management, and no action are reasonable practices. Hotchkiss (2019)
confirmed irrigators using water from Millsite Reservoir are being impacted by deposition even
now. This would factor into sediment management analyses in a detailed study, but RESCON 2
does not currently have a financial, agricultural repercussion resulting from sedimentation.
RESCON 2 Simulated Values and Real Values
The acceptable alternatives for Gebidem Reservoir in RESCON would be no action,
flushing, and HSRS. At Gebidem, flushing is used quite successfully and a sediment balance has
nearly been achieved—that is, outgoing sediments are equal to incoming sediments (Chamoun et
al. 2016; Meile et al. 2014; Emamgholizadeh et al. 2006). The reservoir life is perpetuated
almost indefinitely, yet RESCON suggests the lifetime of Gebidem under a flushing regime
would last about 90 years, clearly shorter than the actual lifetime. Actual data for the other
reservoirs are not currently available, so a complete comparison of RESCON-vs-real values
cannot be compiled. Nonetheless, at least in the case of Gebidem, there is significant disparity
between calculated and real values.
40
Figure 6-1: SMOD with only Millsite Reservoir
Assessing RESCON 2 as a Pre-Feasibility Program
While RESCON matched eight of the ten reservoirs with its analysis to the current
practice, all ten reservoirs practicing sediment management correlated with appropriate SMOD
zones. A reasonable question may then be asked, “If the SMOD requires only three parameters
and RESCON 2 requires 233, why bother using RESCON?” This question is further
strengthened by recalling RESCON does not account for agricultural repercussions from
sedimentation and the disparity between the computed and actual lifetime of Gebidem Reservoir
under a flushing regime.
Although RESCON 2 may not yield information revealed in a detailed analysis, the rapid
assessment and feedback provided by the program are valuable and informative at the conceptual
stage of projects. All of the major sediment management techniques thus far developed can be
0.1
1
10
100
1000
10000
0.0001 0.001 0.01 0.1 1 10
Res
ervo
ir L
ife, y
ears
(sto
rage
cap
acit
y/m
ean
annu
al s
edim
ent i
nflo
w)
Hydraulic Retention Time, years(storage capacity/mean annual runoff)
Flushing, Sluicing, HSRS,Dredging
Bypass, Flushing, Sluicing,Dredging, Density Current,Trucking, Check Dams
Density Current, CatchmentManagement, No Action
Dredging
1
3
2
41
evaluated from both an economic and sustainable development perspective. The SMOD zones
contained the actually used practice in all ten cases but, unlike RESCON, it provides no
economic analysis, is not able to adjust for climate change, does not consider the presence or
absence of low-level outlets, nor does it attempt to organize the various alternatives, in the sense
that some options are likely to be better than others. RESCON 2 can help bridge the gap between
potential alternatives (based on SMOD zones) and knowing which practices to begin
investigating (based on financial appraisals, etc.).
42
7 RECOMMENDATIONS
As RESCON 2 progresses from a beta to fully developed program, a few concerns if
addressed will increase the efficacy of the program and clarity of parameters. Also, using other
tools and models can help create a more complete picture of effects from reservoir sedimentation
and management strategies and account for model insufficiencies in RESCON.
HSRS Operation and Maintenance
Under the “Sediment Management” worksheet, there is no input for HSRS operation and
maintenance (O&M) costs. RESCON assumes negligible costs are associated with HSRS O&M
(Personal communication, Efthymiou 2019), and while they are typically lower than
conventional dredging, they aren’t necessarily insignificant. In one case, Zamora (2018) outlined
and compared O&M costs for HSRS against conventional dredging at the El Canadá hydropower
plant and found HSRS to cost 75% more over a nine-year period. Thus, it is recommended that
an HSRS O&M parameter be added to the program. However, if no such improvement is made,
there are at least two possibilities to account for HSRS O&M costs.
First, users could determine the lifetime of the reservoir using HSRS, estimate the annual
O&M costs, multiply annual O&M costs by the expected lifetime, and add this number to the
initial investment required to install HSRS. The second option is to add HSRS O&M costs to the
total O&M costs of the reservoir under the “Input (Economic Parameters)” worksheet of the
43
program. This latter alternative is discouraged because adjusting total reservoir O&M costs
would affect all sediment management alternatives, not just HSRS. Thus, at least two separate
runs would be needed: one to analyze every other sediment management option, and a second for
HSRS.
Unit Benefit of Reservoir Yield
The “unit benefit of reservoir yield” parameter attempts to account for revenues
associated with multiple reservoir purposes, including drinking water and irrigation supply, flood
control, and hydropower generation (Efthymiou et al. 2017). This single value plays a significant
role in calculating NPVs for all sediment management alternatives. As a pre-feasibility analysis,
users are not required to perform a detailed study to gain accurate measurements of each of the
revenue sources to depict this parameter. Instead, the RESCON 2 user manual provides several
sources for estimating this value, yet none of these references are currently listed or found in the
manual. Additionally, the manual refers to this parameter as “unit benefit of water yield.” Using
the same term in both the program and manual would likely decrease confusion about this
variable.
Because this parameter controls all estimates of NPV, it may be beneficial to expand it
into multiple variables which this parameter is meant to consider. For instance, Table 7-1 gives
specific revenue sources that more clearly indicate which factors apply and potential units for
each respective field.
44
Table 7-1: Potential Expansion of Unit Benefit of Reservoir Yield
Current Parameter Recommended Parameters Unit
Unit benefit of reservoir yield
Hydroelectric generation $/kWh Agricultural use $/m3 Municipality use $/m3
Industrial use $/m3 Flood control $/year
Recreational benefits $/year
Bugs and Treatments
Sensitivity tests indicated the flushing O&M parameter is not factored into the NPV
calculation. For instance, the Tarbela reservoir was run with two very different O&M costs: $0
and $1,000,000,000. The aggregate NPV remained the same for both cases. This phenomenon
was confirmed in other models as well. Additionally, there is a cap on how much sediment
RESCON 2 can handle. For example, the Sanmenxia Reservoir, which is known for having
extremely high sedimentation rates (Wang et al. 2005), could not be simulated without reducing
the mean annual sediment inflow by nearly 40%. It was confirmed and assurance was given that
these were, in fact, bugs in the program and would be treated in later versions of RESCON 2
(Personal communication, Efthymiou 2019). In lieu of this, it may be helpful to include a list of
all RESCON 2 versions with build numbers and bug treatments. This would help users know if
they have the most up-to-date version of the program and if their problem has been resolved with
new builds. Some options for performing this would be GitHub, an open source data
management tool, GitLab, BitBucket, SourceForge, and/or Launchpad. Similarly, having a
system for users to report bugs or suggest recommendations could be helpful to further enhance
RESCON’s efficacy.
45
Using the SMOD with RESCON
In the ten reservoirs analyzed and practicing sediment management, the SMOD zones
contained each of the various practices implemented at each respective reservoir. To minimize
the number of alternatives assessed in RESCON, it is recommended to use the SMOD as an
initial assessment of sediment management alternatives. Then, effort could be spent on obtaining
information for those methods, thus reducing the time needed for developing a model in and
running RESCON.
Looking Beyond RESCON
RESCON uses an empirical approach for sediment trapping and reservoir capacity, as
well as water yield. Using physics-based models can provide details and information not
provided by empirical analyses (for instance, see Salloum and Gharagozloo 2014; Kleinhans and
Van den Berg 2011). Such models will be based on equations for the conservation of mass
(water and sediment) and momentum and will require additional equations for sediment transport
competency and losses due to friction and turbulence.
RESCON attempts to account for environmental and ecological impacts, however, other
tools for directly assessing these effects have been developed and should be considered. For
instance, Glavan et al. (2019) presented a tool for eco-remediation mitigation measures. The
main purpose of the tool was “to support decisions and measures taken to correct defined
problems and to improve water quality and storage capacity in [a] watershed while
minimising[sic] sediment transport.” The tool focused on user-defined critical source areas
within a watershed and showed that sediment inflow could be reduced by up to 30%. As another
example, Sanderson et al. (2011) presented a watershed flow evaluation tool used to evaluate
46
ecological impacts and risks. The tool was implemented in two cases, and successfully assessed
risks across an 840,000-acre watershed but was unable to accomplish this in the other, due to
active channel change and limited data.
47
8 CONCLUSIONS
Annual global reservoir storage capacity loss due to sedimentation is around 40 million
acre-ft (50 km3). Rates of sedimentation vary, but all dams change the natural flow regimes and
can have significant impacts on the local infrastructure, ecology, and environment. Over the last
several decades, several sediment management alternatives have been developed to mitigate
these impacts and prolong the useful life of reservoirs. More recently, focus has shifted from
developing techniques to determining which practices best suit the needs of the reservoir.
RESCON 2 is a pre-feasibility tool meant to help and guide users in a rapid assessment of
potential solutions to the sediment issues experienced at their dam. This analysis of RESCON 2
Beta found the program correctly predicts the actual practice very often.
Several recommendations are suggested to improve or enhance RESCON’s approach to
assess sediment management alternatives. In summary, it is recommended to:
1) Include a parameter for HSRS O&M; 2) Use identical terms for the unit benefit of reservoir yield parameter in both the
model and user manual, and expand this parameter to more explicitly state what this value is meant to consider;
3) Include sources for estimating the unit benefit of reservoir yield in the user manual’s reference list;
4) Incorporate flushing O&M costs to factor into the NPV calculation; 5) Increase the annual sediment inflow capacity to allow for higher sedimentation
rates; 6) Provide a list of RESCON model builds and versions to clearly indicate which bugs
have been treated using GitHub or other open source data management tools; and
48
7) Use the SMOD as an initial pre-feasibility tool to determine sediment management practices to then analyze in RESCON.
The primary limitation to this research was the lack of available data necessary to
compose RESCON models. As already stated, there are some 200+ variables needed to run the
program and limited data is publicly obtainable. Furthermore, of the twenty models analyzed,
only ten practiced sediment management, making it difficult to compare RESCON results
against the ideal alternatives. Having a larger pool of datasets on reservoirs practicing sediment
management would enhance future evaluations of RESCON 2. Additionally, having more
models that span a greater set of sediment management practices could improve analyses. The
majority of reservoirs used in this study and that practiced sediment management used flushing
(60%). By including greater variety in the management type (i.e., reservoirs using bypass
tunnels, catchment management, density current venting, etc.), potential strengths and
weaknesses of the program could become more apparent.
49
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54
APPENDIX A. RESCON 2 MODELS: SEDIMENT MANAGEMENT PRACTICED
Baira Reservoir
Table A-1: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 2,400,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 2,100,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 300,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 2,040,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 1,800,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 240,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 25
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 51 1.1.10 ELMWL [masl] Minimum operation water level 20 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 0 1.1.12 Lres [m] Reservoir length 4,100 1.1.13 ncomp [-] Number of reservoir compartments 5
55
Table A-2: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 1,000 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.50
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
10
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.25
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.30
2.1.2.3 [g/l] Average annual concentration of suspended load
0.270
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10.00 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 500,000,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
56
Table A-3: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 300
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 100
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 2
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 75 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 20 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-4: Sediment Management - Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
75
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
80
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 180,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.005
3.2.2.6 CD [$/m3] Unit cost of dredging 5 3.2.2.7 Shall the unit cost of dredging be determined automatically? Yes 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Active Storage
57
Table A-5: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.46 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
75
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.005
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 0 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 4,100
Table A-6: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
75
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
80
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 180,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Active Storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 90
58
Table A-7: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 3.04 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 5.9 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 75
4.9 C1 [$/a] Total annual operation and maintenance costs 100,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
59
Çubuk Reservoir
Table A-8: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 7,100,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 4,800,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 2,300,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 3,550,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 2,400,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 1,150,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 57
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 907.6 1.1.10 ELMWL [masl] Minimum operation water level 895.0 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 882.6 1.1.12 Lres [m] Reservoir length 6.500 1.1.13 ncomp [-] Number of reservoir compartments 5
60
Table A-9: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 28 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.10
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
10
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.8
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.08
2.1.2.3 [g/l] Average annual concentration of suspended load
2.604
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 3 2.1.2.12 p_b [%] % bedload of total sediment inflow 10.00 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 2,800,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
61
Table A-10: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 180
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 27
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 5
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 99 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 2,000,000 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 895 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? Yes
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-11: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
60
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
90
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.001
3.2.2.6 CD [$/m3] Unit cost of dredging 15 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? Yes
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Active Storage
62
Table A-12: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1.2 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
60
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.001
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 1,000,000 3.2.3.8 DU [Years] The expected life of HSRS 10 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? Yes
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 6,500
Table A-13: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
60
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
90
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 3,600,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 4 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Active storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 30
63
Table A-14: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.46 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 10.0 4.5 Mr [%] Market interest rate of annual retirement fund 10.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.93 4.7 V [$] Decommissioning cost 4,500,000 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 99
4.9 C1 [$/a] Total annual operation and maintenance costs 175,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
64
El Canadá
Table A-15: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 200,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 185,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 15,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 100,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 100,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 0 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 50
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 1,417.5 1.1.10 ELMWL [masl] Minimum operation water level 1,409.0 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 1,407.0 1.1.12 Lres [m] Reservoir length 165 1.1.13 ncomp [-] Number of reservoir compartments 3
65
Table A-16: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 476 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.20
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
15
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.1
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.066
2.1.2.3 [g/l] Average annual concentration of suspended load
0.107
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 23 2.1.2.13 T_b [%] Duration of bedload transport 10 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 95,200,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
66
Table A-15: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
6
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
100
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
58
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 29,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.04
3.2.2.6 CD [$/m3] Unit cost of dredging 2.8 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
Table A-18: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.30 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 100
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.04
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 500,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? Yes
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 165
67
Table A-19: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 27.29 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 6.0 4.5 Mr [%] Market interest rate of annual retirement fund 6.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.2 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 100
4.9 C1 [$/a] Total annual operation and maintenance costs 55,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
68
Gebidem
Table A-20: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 9,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 8,600,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 400,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 8,910,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 8,570,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 340,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 50
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 113 1.1.10 ELMWL [masl] Minimum operation water level 20 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 0 1.1.12 Lres [m] Reservoir length 1,400 1.1.13 ncomp [-] Number of reservoir compartments 5
69
Table A-21: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 429 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.50
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
10
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.35
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.50
2.1.2.3 [g/l] Average annual concentration of suspended load
1.049
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 1 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 214,500,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
70
Table A-22: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 180
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 20
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 2
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 99 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 20 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-23: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
30
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
80
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 300,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.005
3.2.2.6 CD [$/m3] Unit cost of dredging 11.29 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
71
Table A-24: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
2
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.46 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
99
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.005
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 500,000 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 1,400
Table A-25: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
99
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
80
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 300,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13.08 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 80
72
Table A-26: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.54 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 5.9 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 75
4.9 C1 [$/a] Total annual operation and maintenance costs 210,600 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
73
Ichari
Table A-27: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 11,550,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 5,500,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 6,050,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 3,925,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 2,900,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 1,025,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 60
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 37 1.1.10 ELMWL [masl] Minimum operation water level 21 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 0 1.1.12 Lres [m] Reservoir length 11,000 1.1.13 ncomp [-] Number of reservoir compartments 5
74
Table A-28: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 5,300 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.50
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
10
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.25
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
2.20
2.1.2.3 [g/l] Average annual concentration of suspended load
0.374
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 2,650,000,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
75
Table A-29: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 300
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 2,200
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 1
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 75 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 21 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-30: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
75
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
80
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.005
3.2.2.6 CD [$/m3] Unit cost of dredging 5 3.2.2.7 Shall the unit cost of dredging be determined automatically? Yes 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? Yes
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Active storage
76
Table A-31: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.46 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
75
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.005
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 5 3.2.3.8 DU [Years] The expected life of HSRS 100 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 11,000
Table A-32: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
75
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
80
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 1,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Active storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 90
77
Table A-33: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.20 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 3.0 4.5 Mr [%] Market interest rate of annual retirement fund 5.9 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 75
4.9 C1 [$/a] Total annual operation and maintenance costs 250,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
78
Kali Gandaki
Table A-34: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 7,700,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 3,100,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 4,600,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 0 1.1.5 Se_a [m³] Existing active storage of the reservoir 0 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 0 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 100
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 524.0 1.1.10 ELMWL [masl] Minimum operation water level 518.0 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 490.0 1.1.12 Lres [m] Reservoir length 5,000 1.1.13 ncomp [-] Number of reservoir compartments 5
79
Table A-35: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 8,211 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.40
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
15
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.5
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
41.05
2.1.2.3 [g/l] Average annual concentration of suspended load
4.949
2.1.2.3
ExceedT [%] Percentage of time exceeded 15, 30, 50 ExceedMAR [%] Percentage of mean annual water
inflow 50, 24, 12
ExceedMAS [%] Percentage of mean annual sediment inflow
20, 2, 1
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Churchill 2.1.2.11 Brune Curve No [-] 1 2.1.2.12 p_b [%] % bedload of total sediment inflow 1.00 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 3,284,400,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method De-intensification of land use practices
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
5
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
5
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 20,000,000
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
200,000
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management
5
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
81
Table A-37: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 180
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 3,000
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 2
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 1 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 50 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 505 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
2
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-38: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
50
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
50
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 2,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 10 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Bot active and
inactive storage
82
Table A-39: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
2
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 100
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 20,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 5 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table A-40: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
100
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 500,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 12 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 0 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 0
3.3.1.3 Shall the duration and implementation year be defined through economic optimization? No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 0 3.3.1.5 TBP [months] Duration of sediment by-pass 1.0 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 100
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table A-42: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 495 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 0
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 1 3.3.2.6 TSL [months] Duration of sluicing operation 4.00 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 100
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 6.0
84
Table A-43: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 1.00 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 2 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 100
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 4.10 4.3 C2 [$] Total cost of reservoir impoundment 31,591,504 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 6.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 95
4.9 C1 [$/a] Total annual operation and maintenance costs 300,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
86
Millsite Reservoir
Table A-46: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 22,202,640 1.1.2 So_a [m³] Original active storage capacity of the reservoir 15,048,456 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 7,154,184 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 19,005,460 1.1.5 Se_a [m³] Existing active storage of the reservoir 12,881,478 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 6,123,982 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 8
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 1,897.9 1.1.10 ELMWL [masl] Minimum operation water level 1,877.6 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 1,861.7 1.1.12 Lres [m] Reservoir length 2,293 1.1.13 ncomp [-] Number of reservoir compartments 4
87
Table A-47: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 58.9 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.20
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
10.5
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.33
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.121
2.1.2.3 [g/l] Average annual concentration of suspended load
1.847
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water inflow 40, 20, 3 ExceedMAS [%] Percentage of mean annual sediment
inflow 25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 3
2.1.2.12 p_b [%] % bedload of total sediment inflow 10.00 2.1.2.13 T_b [%] Duration of bedload transport 15 2.1.3.1 Zpr Standardized normal nariate at pr*100% 2.33 2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 11,787,582 2.1.3.4 Distribution Distribution of annual inflows Lognormal
88
Table A-48: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
70
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
50
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
44
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 6,621,321 3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.01 3.2.2.6 CD [$/m3] Unit cost of dredging 18.66 3.2.2.7 Shall the unit cost of dredging be determined automatically? No
3.2.2.8 Shall the implementation strategy of dredging be determined through economic optimization?
No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 15 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 15 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Active Storage
Table A-49: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.62 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
50
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.01
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 302,000 3.2.3.8 DU [Years] The expected life of HSRS 60 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 15 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 2,293
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 805,540 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 650,950
3.3.1.3 Shall the duration and implementation year be defined through economic optimization? No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 15 3.3.1.5 TBP [months] Duration of sediment by-pass 1.5 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 50
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 2,293
Table A-51: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.37 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 5.00 4.5 Mr [%] Market interest rate of annual retirement fund 5.90 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 75
4.9 C1 [$/a] Total annual operation and maintenance costs 500,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
90
Sanmenxia
Table A-52: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 9,640,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 7,840,000,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 1,800,000,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 5,590,000,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 5,300,000,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 290,000,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 450
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 335 1.1.10 ELMWL [masl] Minimum operation water level 300 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 280 1.1.12 Lres [m] Reservoir length 114,000 1.1.13 ncomp [-] Number of reservoir compartments 5
91
Table A-53: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 43,036 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.27
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
14
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.4
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
1,000
2.1.2.3 [g/l] Average annual concentration of suspended load
20.913
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 11,619,720,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
92
Table A-54: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 1,600
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 1 3.2.1.3 Qf [m3/s] Representative flushing discharge 2,000
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 123
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 99 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 300 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-55: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
99
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
100
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.02
3.2.2.6 CD [$/m3] Unit cost of dredging 3 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
93
Table A-56: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.4 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 30
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
99
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.02
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 0 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? Yes
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 114,000
Table A-57: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
99
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 500,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Active storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 30
94
Table A-58: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.16 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 5.9 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.2 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 95
4.9 C1 [$/a] Total annual operation and maintenance costs 15,424,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
95
Sefid-Rud
Table A-59: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 1,760,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 1,600,000,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 160,000,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 1,320,000,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 1,270,000,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 50,000,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 500
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 82 1.1.10 ELMWL [masl] Minimum operation water level 30 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 0 1.1.12 Lres [m] Reservoir length 25,000 1.1.13 ncomp [-] Number of reservoir compartments 5
96
Table A-60: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 5,000 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.50
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
10
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.25
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
50
2.1.2.3 [g/l] Average annual concentration of suspended load
9.00
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 2,500,000,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
97
Table A-61: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 100
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 120
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 95 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 30 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-62: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
95
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
80
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 30,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.005
3.2.2.6 CD [$/m3] Unit cost of dredging 5 3.2.2.7 Shall the unit cost of dredging be determined automatically? Yes 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Active storage
98
Table A-63: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.46 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
95
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.005
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 250,000 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 25,000
Table A-64: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
95
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
80
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 30,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Active storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 30
99
Table A-65: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.16 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 5.9 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 75
4.9 C1 [$/a] Total annual operation and maintenance costs 2,816,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
100
Three Gorges
Table A-66: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 39,300,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 23,510,700,859 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 15,789,299,141 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir -- 1.1.5 Se_a [m³] Existing active storage of the reservoir -- 1.1.6 Se_d [m³] Existing inactive storage of the reservoir -- 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 250
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 175 1.1.10 ELMWL [masl] Minimum operation water level 145 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 4 1.1.12 Lres [m] Reservoir length 566,000 1.1.13 ncomp [-] Number of reservoir compartments 5
* Existing storages not displayed because Three Gorges was evaluated as a Greenfield Project
101
Table A-67: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 437,940 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.10
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
18
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.26
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
530
2.1.2.3 [g/l] Average annual concentration of suspended load
1.089
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 43,794,043,200 2.1.3.4 Distribution Distribution of annual inflows Lognormal
102
Table A-68: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 26,000
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 122
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 95 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 145 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table A-69: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
95
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
100
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.02
3.2.2.6 CD [$/m3] Unit cost of dredging 3 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
103
Table A-70: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.4 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 30
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
95
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.02
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 0 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 566,000
Table A-71: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
95
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 500,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Active storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 30
104
Table A-72: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.16 4.3 C2 [$] Total cost of reservoir impoundment 25,000,000,000 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 5.9 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.2 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non
sustainable 75
4.9 C1 [$/a] Total annual operation and maintenance costs 62,880,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
105
APPENDIX B. RESCON 2 MODELS: NO SEDIMENT MANAGEMENT
Abdel Karim
Table B-1: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 11,333,333 1.1.2 So_a [m³] Original active storage capacity of the reservoir 11,333,333 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 0 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 8,866,666 1.1.5 Se_a [m³] Existing active storage of the reservoir 8,866,666 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 0 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 600
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 140 1.1.10 ELMWL [masl] Minimum operation water level 130 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 130 1.1.12 Lres [m] Reservoir length 1,600 1.1.13 ncomp [-] Number of reservoir compartments 5
106
Table B-2: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 48 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.80
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
18
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.2
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.22
2.1.2.3 [g/l] Average annual concentration of suspended load
4.069
2.1.2.3
ExceedT [%] Percentage of time exceeded 25, 50, 75 ExceedMAR [%] Percentage of mean annual water
inflow 35, 18, 10
ExceedMAS [%] Percentage of mean annual sediment inflow
35, 18, 10
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10.00 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 38,400,00 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method De-intensification of land use practices
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
0
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
0
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 0
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
0
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management
1
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
108
Table B-4: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 100
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 30
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 80 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 120 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? Yes
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
42
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-5: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
25
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
5
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
60
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 50,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 2.5 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
109
Table B-6: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
2
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 3 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 100
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
22
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 2,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 10 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table B-7: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
22
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 50,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 10 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 50
110
Table B-8: Sediment Management – Sediment By-pass
ID Parameter Units Description Value
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 150,000,000 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 5,000,000
3.3.1.3 Shall the duration and implementation year be defined through economic optimization?
Yes
3.3.1.4 YearBP Start [years] Implementation year of by-pass 12 3.3.1.5 TBP [months] Duration of sediment by-pass 0.5 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 22
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table B-9: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 135 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 100,000
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 10 3.3.2.6 TSL [months] Duration of sluicing operation 0.50 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 22
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 1.0
111
Table B-10: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 0.50 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 10 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 22
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.21 4.3 C2 [$] Total cost of reservoir impoundment 25,046,666 4.4 r [%] Discount rate 10.0 4.5 Mr [%] Market interest rate of annual retirement fund 12.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.4 4.7 V [$] Decommissioning cost 37,000,000 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 95
4.9 C1 [$/a] Total annual operation and maintenance costs 40,075 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
113
Banja
Table B-13: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 403,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 178,000,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 225,000,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 403,000,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 178,000,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 225,000,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 270
1.1.8 -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 175.0 1.1.10 ELMWL [masl] Minimum operation water level 160.0 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 95.0 1.1.12 Lres [m] Reservoir length 16,000 1.1.13 ncomp [-] Number of reservoir compartments 5
114
Table B-14: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 1,484 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.28
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
14.7
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.4
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
2.42
2.1.2.3 [g/l] Average annual concentration of suspended load
36.000
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Churchill 2.1.2.11 Brune Curve No [-] -- 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 415,520,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method Construction of Check Dams
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
100
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
0
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 20,000,000
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
200,000
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management 5 3.1.10 CL_CM [%] Maximum allowable storage loss before
implementation of catchment management 1
116
Table B-16: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 300
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 5
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 80 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 130 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 110 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
10
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-17: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
50
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
20
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 3.2.2.7 Shall the unit cost of dredging be determined automatically? Yes 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 10 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
117
Table B-18: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 20,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 10 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 17,000
Table B-19: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
80
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
30
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 10,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 10 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 5 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 30,000,000 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 300,000
3.3.1.3 Shall the duration and implementation year be defined through economic optimization? No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 5 3.3.1.5 TBP [months] Duration of sediment by-pass 4.0 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 100
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 17,000
Table B-21: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 168 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 200,000
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 1 3.3.2.6 TSL [months] Duration of sluicing operation 4.00 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 100
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 6.0
119
Table B-22: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 1.00 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 50 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 100
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.36 4.3 C2 [$] Total cost of reservoir impoundment 143,871,000 4.4 r [%] Discount rate 6 4.5 Mr [%] Market interest rate of annual retirement fund 8 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.4 4.7 V [$] Decommissioning cost 50,000,000 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 1,507,500,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 1,507,500,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 500,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 1,253,400,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 1,253,300,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 100,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 1,000
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 810 1.1.10 ELMWL [masl] Minimum operation water level 740 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 710 1.1.12 Lres [m] Reservoir length 20,000 1.1.13 ncomp [-] Number of reservoir compartments 5
122
Table B-26: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 1,050 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.58
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
12
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.2
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
7.00
2.1.2.3 [g/l] Average annual concentration of suspended load
6.00
2.1.2.3
ExceedT [%] Percentage of time exceeded 25, 50, 75 ExceedMAR [%] Percentage of mean annual water
inflow 75, 50, 25
ExceedMAS [%] Percentage of mean annual sediment inflow
60, 30, 25
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10.0 2.1.2.13 T_b [%] Duration of bedload transport 10 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 609,000,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method De-intensification of land use practices
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
5
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
5
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 0 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 0
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
0
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management
1
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
124
Table B-28: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 50
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 2
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 25 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 740 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
5
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-29: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
25
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
1
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 10,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 3.00
3.2.2.6 CD [$/m3] Unit cost of dredging 7 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
125
Table B-30: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
2
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 100
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 2,000,000 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table B-31: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
25
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
1
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 10,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 10 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 0 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 0
3.3.1.3 Shall the duration and implementation year be defined through economic optimization?
No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 1 3.3.1.5 TBP [months] Duration of sediment by-pass 1.0 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 100
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table B-33: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 790 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 100,000
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 1 3.3.2.6 TSL [months] Duration of sluicing operation 1.00 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 25
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 2.0
127
Table B-34: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 0.50 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 1 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 25
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.27 4.3 C2 [$] Total cost of reservoir impoundment 399,861,908 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 6.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 3 4.7 V [$] Decommissioning cost 400,000,000 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 95
4.9 C1 [$/a] Total annual operation and maintenance costs 3,998,619 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
129
Gavins Point Dam
Table B-37: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 709,621,270 1.1.2 So_a [m³] Original active storage capacity of the reservoir 250,291,544 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 459,329,726 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 525,736,802 1.1.5 Se_a [m³] Existing active storage of the reservoir 188,996,721 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 336,740,081 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 2500
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 368.9 1.1.10 ELMWL [masl] Minimum operation water level 363.0 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 352.1 1.1.12 Lres [m] Reservoir length 25,000 1.1.13 ncomp [-] Number of reservoir compartments 5
130
Table B-38: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 28,385 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 1.00
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
30
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.2
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
4.89
2.1.2.3 [g/l] Average annual concentration of suspended load
0.155
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 28,384,760,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
131
Table B-39: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 300
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 1,700
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 14
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 100 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 363 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? Yes
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-40: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
100
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
100
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.02
3.2.2.6 CD [$/m3] Unit cost of dredging 20 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? Yes
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 1 3.2.2.11 Shall a sustainable solution be determined automatically? No 3.2.2.12 Where do you want to perform dredging? Active storage
132
Table B-41: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 0.61 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 30
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.02
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 1,000,000 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? Yes
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 25,000
Table B-42: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
100
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 500,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? No 3.2.4.9 Where do you want to perform trucking? Active storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs 90
133
Table B-43: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.16 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 6 4.5 Mr [%] Market interest rate of annual retirement fund 6 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.2 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 100
4.9 C1 [$/a] Total annual operation and maintenance costs 1,000,000 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
134
Iron Gate
Table B-44: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 100,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 70,000,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 30,000,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 1 1.1.5 Se_a [m³] Existing active storage of the reservoir 1 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 0 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 50
1.1.8 -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 231 1.1.10 ELMWL [masl] Minimum operation water level 200 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 130 1.1.12 Lres [m] Reservoir length 4,800 1.1.13 ncomp [-] Number of reservoir compartments 5
135
Table B-45: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 1,500 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.20
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
20
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.35
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
4.00
2.1.2.3 [g/l] Average annual concentration of suspended load
2.44
2.1.2.3
ExceedT [%] Percentage of time exceeded 30, 60, 90 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 3
ExceedMAS [%] Percentage of mean annual sediment inflow
25, 5, 3
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Churchill 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10.00 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 300,000,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method Construction of Check Dams
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
40
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
20
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 20,000,000
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
200,000
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
Yes
3.1.9 Year CMstart [years] Implementation year of catchment management
5
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
137
Table B-47: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 300
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 180
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 1
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 95 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 180 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? Yes
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
3
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-48: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
80
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
30
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 3,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 3 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 18 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 01 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
138
Table B-49: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
2
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 2 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 100
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
30
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 20,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? Yes
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 2 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table B-50: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
30
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 2,200,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 12 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 30,000,000 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 100,000
3.3.1.3 Shall the duration and implementation year be defined through economic optimization?
No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 4 3.3.1.5 TBP [months] Duration of sediment by-pass 6.0 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 100
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table B-52: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 200 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 15,000,000 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 0
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 10 3.3.2.6 TSL [months] Duration of sluicing operation 4.00 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 100
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 12.0
140
Table B-53: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 6.00 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 1 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 100
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.88 4.3 C2 [$] Total cost of reservoir impoundment 130,937,531 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 6.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 50,000,000 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 95
4.9 C1 [$/a] Total annual operation and maintenance costs 1,309,375 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
142
Mohammed V
Table B-56: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 725,750,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 400,000,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 325,750,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 370,000,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 240,000,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 130,000,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 2,300
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 218 1.1.10 ELMWL [masl] Minimum operation water level 179 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 170 1.1.12 Lres [m] Reservoir length 10,500 1.1.13 ncomp [-] Number of reservoir compartments 5
143
Table B-57: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 750 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.51
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
20
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.2
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
12.8
2.1.2.3 [g/l] Average annual concentration of suspended load
15.36
2.1.2.3
ExceedT [%] Percentage of time exceeded 25, 50, 75 ExceedMAR [%] Percentage of mean annual water
inflow 40, 20, 10
ExceedMAS [%] Percentage of mean annual sediment inflow
40, 20, 10
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 10 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 2.33
2.1.3.2 Gd Gould's correction factor 1.50 2.1.3.3 Sd Standard deviation of annual run-off 382,500,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method De-intensification of land use practices
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
0
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
0
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 0 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 0
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
0
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management
1
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
145
Table B-59: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge 300
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 10
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 1 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 100 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 179 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? No
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
2
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-60: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
25
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
55
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
20
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 100,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 8.53 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 3 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
146
Table B-61: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 75
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 2,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 5 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table B-62: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
70
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
25
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 10,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 1 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 1 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 1,000,000,000 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 5,000,000
3.3.1.3 Shall the duration and implementation year be defined through economic optimization?
No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 5 3.3.1.5 TBP [months] Duration of sediment by-pass 3.0 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 55
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table B-64: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 200 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 100,000
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? Yes
3.3.2.5 YearSL Start [years] Implementation year of sluicing 1 3.3.2.6 TSL [months] Duration of sluicing operation 5.50 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 55
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 6.0
148
Table B-65: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 4.00 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 1 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 70
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.21 4.3 C2 [$] Total cost of reservoir impoundment 0 4.4 r [%] Discount rate 6.0 4.5 Mr [%] Market interest rate of annual retirement fund 7.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.4 4.7 V [$] Decommissioning cost 37,000,000 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non sustainable 95
4.9 C1 [$/a] Total annual operation and maintenance costs 379,926 4.10 4.11 4.12 4.13 Application of declining discount rate? No 4.14 Ymax [years] Maximum duration of financial analysis 300
150
Tarbela
Table B-68: Reservoir Geometry
ID Parameter Units Description Value
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 14,350,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 10,967,000,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 3,383,000,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 9,383,000,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 6,000,000,000 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 3,383,000,000 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 1,650
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 472.4 1.1.10 ELMWL [masl] Minimum operation water level 420.0 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 380.0 1.1.12 Lres [m] Reservoir length 88,000 1.1.13 ncomp [-] Number of reservoir compartments 5
151
Table B-69: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 73,800 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.12
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
15
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.34
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
194.30
2.1.2.3 [g/l] Average annual concentration of suspended load
2.606
2.1.2.3
ExceedT [%] Percentage of time exceeded 16, 32, 44 ExceedMAR [%] Percentage of mean annual water
inflow 58, 30, 8
ExceedMAS [%] Percentage of mean annual sediment inflow
40, 10, 2
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Churchill 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 1.00 2.1.2.13 T_b [%] Duration of bedload transport 5 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 1.64
2.1.3.2 Gd Gould's correction factor 0.60 2.1.3.3 Sd Standard deviation of annual run-off 8,856,000,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method De-intensification of land use practices
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
5
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
5
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 20,000,000
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
200,000
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management
5
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
153
Table B-71: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 380
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 1 3.2.1.3 Qf [m3/s] Representative flushing discharge 3,100
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 30
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 10 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 100 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 390 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? Yes
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
35
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-72: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
50
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
30
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 100,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 5 3.2.2.7 Shall the unit cost of dredging be determined automatically? Yes 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 1 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 10 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
154
Table B-73: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 10
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 20,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 1 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table B-74: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
60
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
30
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 100,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 12 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? No
3.2.4.6 Cycle1TR [years] Implementation year 20 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 10 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 0 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 0
3.3.1.3 Shall the duration and implementation year be defined through economic optimization? No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 1 3.3.1.5 TBP [months] Duration of sediment by-pass 1 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 100
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table B-76: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 436 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 0
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 1 3.3.2.6 TSL [months] Duration of sluicing operation 3 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 100
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 6
156
Table B-77: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 1 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 1 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 100
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.15 4.3 C2 [$] Total cost of reservoir impoundment 2,152,500,000 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 6.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 17,860,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 16,860,000 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 1,000,000 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 0 1.1.5 Se_a [m³] Existing active storage of the reservoir 0 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 0 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location 100
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 637 1.1.10 ELMWL [masl] Minimum operation water level 633 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 614 1.1.12 Lres [m] Reservoir length 9,100 1.1.13 ncomp [-] Number of reservoir compartments 5
159
Table B-81: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 15,667 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume 0.17
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
15
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.5
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
31.50
2.1.2.3 [g/l] Average annual concentration of suspended load
1.709
2.1.2.3
ExceedT [%] Percentage of time exceeded 3, 10, 30 ExceedMAR [%] Percentage of mean annual water
inflow 86, 64, 32
ExceedMAS [%] Percentage of mean annual sediment inflow
40, 25, 14
2.1.2.4 pcl [%] % clay of suspended sediment inflow -- 2.1.2.5 psi [%] % silt of suspended sediment inflow -- 2.1.2.6 psa [%] % sand of suspended sediment inflow -- 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles -- 2.1.2.8 ws_si [m/s] Settling velocity of silt particles -- 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles -- 2.1.2.10 TE_Method Trap efficiency method Churchill 2.1.2.11 Brune Curve No [-] 1 2.1.2.12 p_b [%] % bedload of total sediment inflow 15.00 2.1.2.13 T_b [%] Duration of bedload transport 30 2.1.3.1 Zpr Standardized normal nariate at
pr*100% 1.64
2.1.3.2 Gd Gould's correction factor 0.60 2.1.3.3 Sd Standard deviation of annual run-off 2,663,390,000 2.1.3.4 Distribution Distribution of annual inflows Lognormal
3.1.1 CM_Method [-] Catchment management method De-intensification of land use practices
3.1.2 MASb reduction [%] Expected reduction of bedload inflow in reservoir due to catchment management
5
3.1.3 MASs reduction [%] Expected reduction of suspended load inflow in reservoir due to catchment management
5
3.1.4 YearMAS reduction Start
[Years] How many years after its implementation will catchment management affect sediment inflow in reservoir?
1
3.1.5 3.1.6 C_CM [US$] Costs for implementation of catchment
management measures 20,000,000
3.1.7 OMC_CM [US$/a] Annual operation and maintenance costs of catchment management
200,000
3.1.8 Shall the implementation year of catchment management be determined through economic optimization?
No
3.1.9 Year CMstart [years] Implementation year of catchment management
5
3.1.10 CL_CM [%] Maximum allowable storage loss before implementation of catchment management
100
161
Table B-83: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 300
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 1 3.2.1.3 Qf [m3/s] Representative flushing discharge 2,000
3.2.1.4 Tf [days] Duration of flushing after complete drawdown 10
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 1 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 50 3.2.1.7 s1 [%] Fraction of run-of-river benefits 50 3.2.1.8 s2 [%] Fraction of storage benefits 50 3.2.1.9 FI [US$] Cost of capital investment 0 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 614 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization? Yes
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
14
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing 0
Table B-84: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
100
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
100
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 6,500,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.00
3.2.2.6 CD [$/m3] Unit cost of dredging 10 3.2.2.7 Shall the unit cost of dredging be determined automatically? No 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization? No
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 2 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 2 3.2.2.11 Shall a sustainable solution be determined automatically? Yes 3.2.2.12 Where do you want to perform dredging? Both active and
inactive storage
162
Table B-85: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
2
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 1 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 100
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.00
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 20,000,000 3.2.3.8 DU [Years] The expected life of HSRS 20 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization? No
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 5 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table B-86: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
100
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 10,000,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 12 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization? Yes
3.2.4.6 Cycle1TR [years] Implementation year 4 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 3 3.2.4.8 Shall a sustainable solution be determined automatically? Yes 3.2.4.9 Where do you want to perform trucking? Both active and
inactive storage 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
3.3.1.1 CB-P [US$] Cost for implementation of by-pass structure 50,000,000 3.3.1.2 OMCB-P [US$/a] Annual operation and maintenance Costs of by-
pass structures 5,000,000
3.3.1.3 Shall the duration and implementation year be defined through economic optimization? No
3.3.1.4 YearBP Start [years] Implementation year of by-pass 1 3.3.1.5 TBP [months] Duration of sediment by-pass 6.0 3.3.1.6 CLB-P [%] Maximum allowable storage loss before
implementation of sediment by-pass 20
3.3.1.7 TB-P max [months] Maximum allowable duration of by-pass operation
3.3.1.11 BPlimit [m] Length limit for feasibility of by-pass structure 5,000
Table B-88: Sediment Management – Sluicing
ID Parameter Units Description Value
3.3.2.1 ELSL [masl] Reservoir pool elevation during sluicing 633 3.3.2.2 CSL [US$] Cost for implementation of sluicing structure 0 3.3.2.3 OMCSL [US$/a] Annual operation and maintenance costs of sluicing
structures 0
3.3.2.4 Shall the duration and implementation year be defined through economic optimization? No
3.3.2.5 YearSL Start [years] Implementation year of sluicing 1 3.3.2.6 TSL [months] Duration of sluicing operation 3.00 3.3.2.7 CLSL [%] Maximum allowable storage loss before implementation of
sluicing 100
3.3.2.8 TSL max [months] Maximum allowable duration of sluicing 4.0
164
Table B-89: Sediment Management – Density Current Venting
ID Parameter Units Description Value
3.3.3.1
3.3.3.2 TDCV [months] Duration of density current venting 1.00 3.3.3.3 YearDCVstart [years] Implementation year of denstiy current venting 1 3.3.3.4 CLDCV [%] Maximum allowable storage loss before implementation of
density current venting 100
3.3.3.5 sDCV [%] Fraction of reservoir benefits the year density current venting occurs
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 2.65 4.3 C2 [$] Total cost of reservoir impoundment 47,350,355 4.4 r [%] Discount rate 5.0 4.5 Mr [%] Market interest rate of annual retirement fund 6.0 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.1 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 2,452,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 1,517,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location
1.1.8 -- -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 80 1.1.10 ELMWL [masl] Minimum operation water level 77.43 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 70.2 1.1.12 Lres [m] Reservoir length 5,000 1.1.13 ncomp [-] Number of reservoir compartments 5
167
Table C-2: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.20
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
0.006
2.1.2.3 [g/l] Average annual concentration of suspended load
2.1.2.3
ExceedT [%] Percentage of time exceeded ExceedMAR [%] Percentage of mean annual water
inflow
ExceedMAS [%] Percentage of mean annual sediment inflow
2.1.2.4 pcl [%] % clay of suspended sediment inflow 2.1.2.5 psi [%] % silt of suspended sediment inflow 2.1.2.6 psa [%] % sand of suspended sediment inflow 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles 2.1.2.8 ws_si [m/s] Settling velocity of silt particles 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 2.1.2.13 T_b [%] Duration of bedload transport 2.1.3.1 Zpr Standardized normal nariate at
pr*100%
2.1.3.2 Gd Gould's correction factor 2.1.3.3 Sd Standard deviation of annual run-off 2.1.3.4 Distribution Distribution of annual inflows
168
Table C-3: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge
3.2.1.4 Tf [days] Duration of flushing after complete drawdown
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 100 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 77.43 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization?
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing
Table C-4: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
100
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
100
3.2.2.4 MD [m3] Amount of sediment removed per dredging event 1,000,000
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.02
3.2.2.6 CD [$/m3] Unit cost of dredging 3.00 3.2.2.7 Shall the unit cost of dredging be determined automatically? 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization?
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 3.2.2.11 Shall a sustainable solution be determined automatically? 3.2.2.12 Where do you want to perform dredging?
169
Table C-5: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 1 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 30
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.02
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization?
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS 5,000
Table C-6: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
100
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 500,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13.00 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization?
3.2.4.6 Cycle1TR [years] Implementation year 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 3.2.4.8 Shall a sustainable solution be determined automatically? 3.2.4.9 Where do you want to perform trucking? 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs
170
Table C-7: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 3.02 4.3 C2 [$] Total cost of reservoir impoundment 4.4 r [%] Discount rate 6 4.5 Mr [%] Market interest rate of annual retirement fund 6 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.2 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non
1.1.1 So_gr [m³] Original gross storage capacity of the reservoir 252,000,000 1.1.2 So_a [m³] Original active storage capacity of the reservoir 1.1.3 So_d [m³] Original inactive storage capacity of the reservoir 1.1.4 Se_gr [m³] Existing gross storage capacity of the reservoir 80,000,000 1.1.5 Se_a [m³] Existing active storage of the reservoir 1.1.6 Se_d [m³] Existing inactive storage of the reservoir 1.1.7 Wbot [m] Representative reservoir bottom width at the dam
location
1.1.8 -- -- --
1.1.9 ELOWL [masl] Maximum pool elevation of reservoir 245 1.1.10 ELMWL [masl] Minimum operation water level 173 1.1.11 Elbmin [masl] Minimum reservoir bed elevation at dam site 102 1.1.12 Lres [m] Reservoir length 1.1.13 ncomp [-] Number of reservoir compartments 5
172
Table C-9: Hydrology and Sediment
ID Parameter Units Description Value
2.1.1.1 MAR [million m³/a] Mean annual reservoir water inflow 2.1.1.2 Cv [-] Coefficient of variation of annual run-
off volume
2.1.1.3 Twater [°C] Representative water temperature in the reservoir
2.1.2.1 rd [tonnes/m³] Specific weight of in-situ reservoir sediment (bulk density)
1.12
2.1.2.2 MAS [million tonnes/a] Mean annual total (suspended and bedload) sediment inflow mass
2.1.2.3 [g/l] Average annual concentration of suspended load
2.1.2.3
ExceedT [%] Percentage of time exceeded ExceedMAR [%] Percentage of mean annual water
inflow
ExceedMAS [%] Percentage of mean annual sediment inflow
2.1.2.4 pcl [%] % clay of suspended sediment inflow 2.1.2.5 psi [%] % silt of suspended sediment inflow 2.1.2.6 psa [%] % sand of suspended sediment inflow 2.1.2.7 ws_cl [m/s] Settling velocity of clay particles 2.1.2.8 ws_si [m/s] Settling velocity of silt particles 2.1.2.9 ws_sa [m/s] Settling velocity of sand particles 2.1.2.10 TE_Method Trap efficiency method Brune 2.1.2.11 Brune Curve No [-] 2 2.1.2.12 p_b [%] % bedload of total sediment inflow 2.1.2.13 T_b [%] Duration of bedload transport 2.1.3.1 Zpr Standardized normal nariate at
pr*100%
2.1.3.2 Gd Gould's correction factor 2.1.3.3 Sd Standard deviation of annual run-off 2.1.3.4 Distribution Distribution of annual inflows
173
Table C-10: Sediment Management – Flushing
ID Parameter Units Description Value
3.2.1.1 Y [-] Indicator of deposits type 650
3.2.1.2 Ans 3 or 1 Sediment removal difficulty 3 3.2.1.3 Qf [m3/s] Representative flushing discharge
3.2.1.4 Tf [days] Duration of flushing after complete drawdown
3.2.1.5 Cal_SSfl [-] Calibration parameter for Mignot equation 3.2.1.6 CLF [%] Maximum percent of capacity loss allowable 100 3.2.1.7 s1 [%] Fraction of run-of-river benefits 90 3.2.1.8 s2 [%] Fraction of storage benefits 90 3.2.1.9 FI [US$] Cost of capital investment 3.2.1.10 Elfl_dam [masl] Water elevation at dam during flushing 3.2.1.12 Shall the implementation strategy of flushing be determined through economic
optimization?
3.2.1.13 CycleNS [Years] Time interval between flushing events during the 1st phase (Reservoir storage > sustainable long term reservoir capacity)
1
3.2.1.14 CycleS [Years] Time interval between flushing events during the 2nd phase (Reservoir storage < sustainable long term reservoir capacity)
1
3.2.1.15 OMC_FL [US$/a] Annual operation and maintenance costs of flushing
Table C-11: Sediment Management – Dredging
ID Parameter Units Description Value
3.2.2.1 Cw [%] Concentration by weight of sediment removed to water removed by traditional dredging
30
3.2.2.2 CLD [%] Maximum percent of capacity loss that is allowable at any time in reservoir for dredging
100
3.2.2.3 ASD [%] Maximum percent of reservoir storage that can be restored during each dredging event
1,000,000
3.2.2.4 MD [m3] Amount of sediment removed per dredging event
3.2.2.5 PD [$/m3] Unit value of water used in dredging operations 0.02
3.2.2.6 CD [$/m3] Unit cost of dredging 3.00 3.2.2.7 Shall the unit cost of dredging be determined automatically? 3.2.2.8 Shall the implementation strategy of dredging be determined through economic
optimization?
3.2.2.9 Cycle1DR [years] Duration of phase 1 (No dredging) 3.2.2.10 Cycle2DR [years] Cycle length in phase 2 (Dredging operation) 3.2.2.11 Shall a sustainable solution be determined automatically? 3.2.2.12 Where do you want to perform dredging?
174
Table C-12: Sediment Management – HSRS
ID Parameter Units Description Value
3.2.3.1 Type 1 or 2 Sediment type category to be removed by Hydrosuction Sediment Removal System (HSRS)
1
3.2.3.2 D [m] Assume a trial pipe diameter for HSRS 3.2.3.3 NP 1, 2, or 3 Number of pipes for HSRS 3.2.3.4 YA [%] Maximum fraction of total yield that is allowed to be
used in HSRS operations 30
3.2.3.5 CLH [%] Maximum percent of capacity loss that is allowable at any time in reservoir for HSRS
100
3.2.3.6 PH [$/m3] Unit value of water released downstream of dam in river by HSRS operations
0.02
3.2.3.7 HI [US$] Cost of capital investment to install HSRS 3.2.3.8 DU [Years] The expected life of HSRS 25 3.2.3.9 Shall the implementation strategy of HSRS be determined through economic
optimization?
3.2.3.10 Year HSRSstart [Years] Timing of HSRS installation 3.2.3.11 HSRSlimit [m] Length limit for implementation of HSRS
Table C-13: Sediment Management – Trucking
ID Parameter Units Description Value
3.2.4.1 CLT [%] Maximum percent of capacity loss that is allowable at any time in reservoir for trucking
100
3.2.4.2 AST [%] Maximum percent of reservoir storage that can be restored during each trucking event
100
3.2.4.3 MT [m3] Amount of sediment removed per trucking event 500,000 3.2.4.4 CT [US$/m3] Unit Cost of trucking 13.00 3.2.4.5 Shall the implementation strategy of trucking be determined through economic
optimization?
3.2.4.6 Cycle1TR [years] Implementation year 3.2.4.7 Cycle2TR [years] Frequency of trucking operation 3.2.4.8 Shall a sustainable solution be determined automatically? 3.2.4.9 Where do you want to perform trucking? 3.2.4.10 sTR [%] Fraction of reservoir water yield the year trucking
occurs
175
Table C-14: Economic Parameters
ID Parameter Units Description Value
4.1 4.2 c [$/m3] Unit cost of construction per m3 of reservoir capacity 0.16 4.3 C2 [$] Total cost of reservoir impoundment 4.4 r [%] Discount rate 6 4.5 Mr [%] Market interest rate of annual retirement fund 6 4.6 P1 [$/m3] Unit benefit of reservoir yield 0.2 4.7 V [$] Decommissioning cost 0 4.8 CL_NS [%] Capacity loss for characterization of a reservoir as non
